Hydrocarbons occur in deposits located within the earth. Hydrocarbons may be found at many different depths and pressures and can have a wide range of inherent characteristics. Many hydrocarbon deposits, when first discovered, are fluid enough to be removed from the underground formation, by simple means, such as pumping. However, as the existing reservoirs are pumped down, such easy to recover mobile hydrocarbons become depleted. What is left behind as a relatively immobile in situ fraction may be a significant percentage of the original hydrocarbon deposit.
Other hydrocarbon deposits, such as tar sands deposits, are simply not fluid enough to be pumped in the first place. In this case, other recovery techniques, such as surface mining are preferred. However, many deposits, including a large majority of tar sand deposits in Alberta are buried too deeply to make surface mining viable.
It has long been recognized that methods of enhanced recovery are required to mobilize the otherwise insufficiently mobile in situ hydrocarbons. Various techniques have been developed and used, including methods to try to physically push the less mobile hydrocarbons, such as with water floods, gas injection or the like, or methods to change the viscosity of the hydrocarbons, such as by applying heat, solvents or the like. In the tar sands, in particular, heat has been applied by means of steam, in steam assisted gravity drainage (SAGD), by means of firefloods, such as toe-to-heel air injection (THAI). Solvent stimulations have also been tried, with unheated vapour stimulations, such as (VAPEX), and more recently the present inventor has proposed the use of heated vapourized solvents under condensing conditions (N-SOLV) as set out in prior Canadian patent applications 2,235,085, 2,299,790, 2,351,148, 2,374,115. An apparatus and method of testing in situ extraction processes by the present inventor is described in Canadian 2,436,158. What all of these prior extraction methods have in common is the attempt to cause the in situ hydrocarbons to flow, or to be mobile enough to be economically recovered. Flowing hydrocarbons can be recovered, for example through gravity drainage through the underground reservoir to a production well and then by pumping or some other lifting means to surface facilities.
A difficulty with the design of an extraction or hydrocarbon recovery process and an associated surface facility is understanding precisely what stimulative effect any such process is likely to have on the in situ hydrocarbons. In particular with gravity drainage processes, it is not clear, up to now, what precise effect the solvent has on hydrocarbons or what solvent characteristics are desired or required. Some gravity drainage processes use cold solvent vapour, others use heat and solvent vapour and liquid, others use heat, solvent and water, and others use just heat and water and yet others use combustion or electrical heat to mobilize the hydrocarbon. Some process candidates have a considerable solvent effect, whereas others, such as steam are not soluble per se in the hydrocarbons.
Although various numerical simulations have been developed and are used by researchers to model solvent based gravity drainage processes to try to predict extraction rates, the predictive ability of such numerical models has until now been poor. The numerical models rely on certain assumptions about the extraction mechanism. Field implementations of solvent based gravity processes which are designed using such numerical computer models, have, up until now, not worked as predicted by the models. To add predictability, laboratory testing has also been done of proposed processes, which attempt to simulate field conditions. However, the computer models have so many adjustable parameters that are used to tune the models to measured data, it is not possible to identify reliable experiments from outliers. What is required is a better understanding of the effect of various process parameters on in situ based extraction processes such as solvent processes, so better and more reliable extraction rate predictions can be made.
Many laboratory experiments that have been performed on solvent-based recovery processes have had results which have been published. However, the data from the various experiments is scattered and unconnected. The results of packed bed experiments (either glass bead or sand pack) are inconsistent with the results of Hele-Shaw experiments (oil sandwiched between two glass plates). The results of using one type of solvent at one reservoir condition do not correlate to the use of a different solvent at different reservoir conditions. As a result, the present approach for the industry is very laborious with significant efforts required on a case by case basis to develop an effective process. Furthermore, certain aspects of field (i.e. large) scale underground conditions cannot be accurately reproduced in smaller scale laboratory tests due to boundary conditions, scale-up issues and the like. To date laboratory test results have also not translated well into field results. Since both numerical and experimental results cannot be relied upon, the design and development of new gravity based drainage processes has struggled. The costs of field testing new processes do not warrant the risks inherent with an unpredictable result. Consequently a reliable means for predicting the extraction rates of any given gravity drainage process is very desirable.
As a result, at present there is no accurate way to predict extraction rates for new processes or even reliably estimate what effect changing process parameters, such as solvent choice, extraction pressure and temperature, might have on extraction rates, short of actually trying out the process in the field in a demonstration plant. Field demonstrations of an extraction technology can cost 50-100 million dollars and this entry cost is a barrier to obtaining additional insights into process dynamics. What is desired, is a way of correlating the data of the wide range of experimental production results to understand better the key parameters governing the effectiveness of new extraction processes based on gravity drainage. To date, not only has this not been achieved, it has not been thought possible.
As a consequence of this lack of predictability, industry has resorted to high energy intensity extraction techniques. In the case of steam assisted gravity drainage (“SAGD”), for example, the injected steam can be heated to temperatures in excess of 250 degrees centigrade to deliver as much heat as possible into the formation. Water is preferred as the heat transfer fluid due to its high latent heat capacity. SAGD has proven to be able to extract the in situ hydrocarbons, but requires large amounts of energy, high pressures and good confinement, thick pay zones and the consumption of scarce water resources to conduct the extraction. Consequently the tar sands have been labeled by some environmentalists as one of the dirtiest sources of hydrocarbons in the world. Further, the steam extraction process recovers to the surface all of the unwanted heavy fractions from the in situ hydrocarbons which are subsequently rejected as waste coke, contain toxic metals and sulphur and are placed in vast holding ponds or lagoons on the surface.
What is required is a better understanding of the in situ processes on the in situ hydrocarbons, so a more predictable approach to hydrocarbon extraction can be designed and implemented. Although a heated condensing solvent process offers a lower energy alternative to SAGD for example, and has some promise it is not clear short of a field demonstration plant what extraction results can be expected. Current computer and numerical models predict that it does not provide any advantage relative to unheated solvent vapour extraction whereas lab data shows that it can be commercially attractive. What is needed is a better understanding of all of the prior experimental work, a reconciliation of the apparent discrepancies and thus an improved understanding of what factors are important to an in situ solvent extraction process so that reliable extraction results can be predicted and the factors which affect extraction rates can be better understood.